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Current position

Research interest

Website

Positions/functions as a policy advisor

Member, National Academies Sciences, Committee on National Statistics, Standing
Committee on the Future of Major NSF-Funded Social Surveys, September 1, 2015 to
October 31, 2016; Co-Research Director, CWICstat, 2009–2014; Committee on National
Statistics of the National Academy of Science Panel, “Assessing the Benefits of the
American Community Survey for the NSF Survey of College Graduates,” 2007–2009

Matching avoids making assumptions about the
functional form of the regression equation, making analysis more
reliable

“Matching” is a statistical technique used to
evaluate the effect of a treatment by comparing the treated and non-treated
units in an observational study. Matching provides an alternative to older
estimation methods, such as ordinary least squares (OLS), which involves
strong assumptions that are usually without much justification from economic
theory. While the use of simple OLS models may have been appropriate in the
early days of computing during the 1970s and 1980s, the remarkable increase
in computing power since then has made other methods, in particular
matching, very easy to implement.